Automated Strip Break Classification in Cold Rolling Mills

This technical report presents a novel methodology for automated classification of strip breaks in tandem cold rolling mills using Falkonry's time series AI platform. Strip breaks, which are common during the cold rolling process, can lead to significant productivity losses, equipment damage, and safety hazards. The report outlines the challenges associated with manual diagnosis of strip breaks, which is time-consuming and less accurate, requiring extensive human resources. The proposed solution leverages existing PLC data to enable real-time classification of strip breaks, allowing operations teams to quickly identify underlying causes and implement corrective actions. The methodology aims to improve productivity by reducing the time needed for diagnosis and recovery from strip break events. Additionally, the report details the advantages of using off-the-shelf technology for faster deployment and competency development within operations teams. The findings indicate a potential for substantial improvements in production efficiency and a reduction in the required workforce for analysis.